On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Communications of the ACM
Mining Graph Data
Proceedings of the 15th international conference on World Wide Web
Approximation algorithms for combinatorial problems
Journal of Computer and System Sciences
UMCC-DLSI: Integrative resource for disambiguation task
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
Word sense disambiguation: a graph-based approach using N-Cliques partitioning technique
NLDB'11 Proceedings of the 16th international conference on Natural language processing and information systems
A graph-based approach to WSD using relevant semantic trees and n-cliques model
CICLing'12 Proceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
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In social network analysis, a k-clique is a relaxed clique, i.e., a k-clique is a quasi-complete sub-graph. A k-clique in a graph is a sub-graph where the distance between any two vertices is no greater than k. The visualization of a small number of vertices can be easily performed in a graph. However, when the number of vertices and edges increases the visualization becomes incomprehensible. In this paper, we propose a new graph mining approach based on k-cliques. The concept of relaxed clique is extended to the whole graph, to achieve a general view, by covering the network with k-cliques. The sequence of k-clique covers is presented, combining small world concepts with community structure components. Computational results and examples are presented.